Assessment methods for rehabilitation and recovery have recently been the focal point of research for medical professionals and engineers alike. Current assessment protocols rely on historical ordinal metrics which ha...
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ISBN:
(数字)9781728134581
ISBN:
(纸本)9781728134598
Assessment methods for rehabilitation and recovery have recently been the focal point of research for medical professionals and engineers alike. Current assessment protocols rely on historical ordinal metrics which have been disputed despite their inter-rater reliability. Contemporary kinematic measures have allowed for new approaches to assess recovery progress. However, the abundance of data has deterred medical professionals from adopting these new protocols. This paper presents a method, based on the RMSE-LWSS (Longest Warping Subsequence) score, to distinguish outliers from systemic change for updating the personalized exercise path for users. By treating change detection as a classification problem, the incorporation of a compromised path based on the user's current capability is possible. Experiments were conducted to verify the efficacy of the method, comparing against statistical techniques for change detection and classification of pre-determined paths. The paper highlights how readily available data, rather than complex sensor systems, can be utilized to improve the robustness of personalization capabilities for robotic rehabilitation systems.
This paper describes a novel probabilistic approach to incorporating odometric information into appearance-based SLAM systems, without performing metric map construction or calculating relative feature geometry. The p...
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This paper describes a novel probabilistic approach to incorporating odometric information into appearance-based SLAM systems, without performing metric map construction or calculating relative feature geometry. The proposed system, dubbed Continuous Appearance-based Trajectory SLAM (CAT-SLAM), represents location as a probability distribution along a trajectory, and represents appearance continuously over the trajectory rather than at discrete locations. The distribution is evaluated using a Rao- Blackwellised particle filter, which weights particles based on local appearance and odometric similarity and explicitly models both the likelihood of revisiting previous locations and visiting new locations. A modified resampling scheme counters particle deprivation and allows loop closure updates to be performed in constant time regardless of map size. We compare the performance of CAT-SLAM to FAB-MAP (an appearance-only SLAM algorithm) in an outdoor environment, demonstrating a threefold increase in the number of correct loop closures detected by CAT-SLAM.
Smart sensors and medical health technologies are becoming increasingly popular due to their potential for real-time, non-invasive health monitoring and diagnostics. With the integration of Artificial Intelligence (AI...
ISBN:
(数字)9781837242863
Smart sensors and medical health technologies are becoming increasingly popular due to their potential for real-time, non-invasive health monitoring and diagnostics. With the integration of Artificial Intelligence (AI), these devices can track vital signs and important biomarkers, supporting the management of chronic diseases. This study employs bibliometric analysis using tools like VOSviewer to map research trends in this domain, identifying collaborations, emerging keywords, and contributions from institutions and countries. Findings indicate a significant increase in publications and citations, especially after 2010, highlighting influential journals such as IEEE Sensors Journal. The primary focus is on health monitoring applications and advancements in sensor technology, with an increasing use of terms like "machine learning" and "data analytics." These findings provide insights into future research directions and technological innovations that impact medical health applications. It is recommended that future development integrate advanced data processing techniques and apply sensors in infrastructure and smart city environments, aiming to create systems that are more responsive, efficient, and sustainable.
The paper presents an implementation of supervisory controllers in the IEC 61131-3 compliant programming environment. The implemented model-based approaches provide particularly simple methods for constructing feedbac...
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The paper presents an implementation of supervisory controllers in the IEC 61131-3 compliant programming environment. The implemented model-based approaches provide particularly simple methods for constructing feedback controllers for untimed and timed discrete event systems modeled by Petri nets. Programs written in Matlab 5.3/6.1 have been used to solve the OFFLINE supervisory control synthesis and supervisor simulation. The implementation of the designed supervisory controller can be performed in an IEC 61131-3 compliant programming environment with help of a quick PLC controller, or a quick dedicated controller.
Large scale antenna systems are used to exploit spatial multiplexing gains in massive MIMO systems. To realise those gains, channel state information has to be acquired at a base station. However, an initial control c...
ISBN:
(数字)9788831299008
ISBN:
(纸本)9781728137124
Large scale antenna systems are used to exploit spatial multiplexing gains in massive MIMO systems. To realise those gains, channel state information has to be acquired at a base station. However, an initial control channel has to be provided to synchronise time and frequency at the user. This control channel should be undirected to cover the base stations operational area and can therefore not exploit the coherent array gain without additional strategies. Beam sweeping has been proposed to provide increased spatial coverage. Its performance for large scale antenna systems in Rayleigh and Rician fading environments is analysed. Even an orthogonal basis of antenna weights for full spatial coverage can not provide the full array gain. The results quantity the gap between achievable synchronisation and full array gain for uncorrelated antennas. Closed form solutions for the distribution of the gain gap under Rayleigh fading conditions are derived.
This study investigates the effects of occlusions on the fairness of face recognition systems, particularly focusing on demographic biases. Using the Racial Faces in the Wild (RFW) dataset and synthetically added real...
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ICA (Independent Component Analysis) can separate unknown source signals from their mixture signals without information on the transfer functions, provided that the sources are statistically independent. When the numb...
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ICA (Independent Component Analysis) can separate unknown source signals from their mixture signals without information on the transfer functions, provided that the sources are statistically independent. When the number of the source signals is equal to that of the observed signals, the original sources can be recovered except for indeterminacy of scale and permutation. However, the number of the sources is unknown in a real environment. In this paper, we propose an estimation method for the number of the sources based on the joint distribution of the observed signals under two-sensor configuration. From several simulation results, it is found that the number of the sources is coincident to that of peaks in the histogram of the distribution
The rail industry requires robust technology to support environmentally friendly and sustainable transportation, of which diesel generators are a key component. Currently, maintenance approaches for railway diesel gen...
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ISBN:
(数字)9798331521219
ISBN:
(纸本)9798331521226
The rail industry requires robust technology to support environmentally friendly and sustainable transportation, of which diesel generators are a key component. Currently, maintenance approaches for railway diesel generators tend to use preventive strategies that are less efficient and costly. Therefore, this study proposes the estimation of diesel generator health indicators to support predictive maintenance by utilizing multivariate stochastic approaches and exponential-based degradation models. This degradation model contains deterministic and stochastic parameters estimated using Bayes filter. In addition, to improve forecasting accuracy, this approach involves more than one type of measurement variable data and applies one of the multivariate analysis techniques, namely principal component analysis (PCA). The PCA variables are then used to determine the health indicators of diesel generators. As a case study, this research was conducted using data from a diesel generator on a power car. The results show that the health indicator is obtained when the tresshold has been reached.
Detecting 3D objects is a core task for autonomous vehicles (AVs), as it allows them to drive safely and responsibly. To detect objects quickly and accurately, AVs have LiDAR sensors, which can capture 3D data from 36...
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